Locking Down Violence: The COVID-19 Pandemic's Impact on Non-State Actor Violence
In: American Political Science Review 2023 (open access)
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In: American Political Science Review 2023 (open access)
SSRN
In: Comparative political studies: CPS, Band 46, Heft 1, S. 3-30
ISSN: 0010-4140
World Affairs Online
In: Comparative political studies: CPS, Band 46, Heft 1, S. 3-30
ISSN: 1552-3829
The literature holds that coalition-building parties prefer the policy distance of coalition partners to be as small as possible. In light of continued importance of religion in electoral politics cross-nationally, the distance argument is worrisome for minorities seeking political access because many minorities are of different religion than the majority representatives forming coalitions. The authors suggest plurality parties' objectives to demonstrate inclusiveness outweigh the concern over policy distance. They test their hypotheses on a sample of all electorally active ethnic minorities in democracies from 1945 to 2004. The authors find support for their hypothesis that ethnic parties representing minorities that diverge in religious family from the majority are more likely to be included in governing coalitions than are ethnic minorities at large. It is interesting, however, that they also find that minority parties representing ethnic groups that differ in denomination from the majority are less likely to be included in governing coalitions.
In: Party politics: an international journal for the study of political parties and political organizations, Band 17, Heft 2, S. 243-260
ISSN: 1460-3683
Is ethnic social diversity relevant to cross-national variation in economic development, or is the inclusion or exclusion of said groups in political decision-making the more salient factor? We argue that deleterious policy effects resulting in diminished economic growth are caused by exclusion of mobilized ethnic groups from the policy process and not just ethnic social diversity per se. Conversely, a positive impact of ethnicity as more groups are included in the policy process with increasing access to cabinet is due, first, to the fact that a population finding its preferences represented in the policy process likely supports implementation of resultant policy. Second, the policy quality likely improves with greater variety in input. Third, a greater number of included ethnic groups in cabinet increases the number of ethnic partisan veto players in the policy process — thereby generating increased policy stability in the long term. We test this idea first on long-run growth in democracy and, second, on annual indicators of growth. We find that increasing ethnic social fragmentation still negatively impacts on the economy. However, cabinet diversity offsets some of these negative effects as it improves growth of GDP per capita.
In: Party politics: an international journal for the study of political parties and political organizations, Band 17, Heft 2, S. 243-261
ISSN: 1354-0688
In: The association for the study of nationalities
World Affairs Online
In: Ethnopolitics, Band 16, Heft 1, S. 1-4
ISSN: 1744-9065
In: Ethnopolitics, Band 20, Heft 2, S. 216-243
ISSN: 1744-9065
In: Ethnopolitics, Band 20, Heft 2, S. 216-243
ISSN: 1744-9065
World Affairs Online
In: Terrorism and political violence, Band 25, Heft 1, S. 29-52
ISSN: 1556-1836
In: Research Policy, Band 34, Heft 10, S. 1570-1590
In: The journal of conflict resolution: journal of the Peace Science Society (International), Band 62, Heft 1, S. 203-226
ISSN: 1552-8766
The article introduces the All Minorities at Risk (AMAR) data, a sample of socially recognized and salient ethnic groups. Fully coded for the forty core Minorities at Risk variables, this AMAR sample provides researchers with data for empirical analysis free from the selection issues known in the study of ethnic politics to date. We describe the distinct selection issues motivating the coding of the data with an emphasis on underexplored selection issues arising with truncation of ethnic group data, especially when moving between levels of data. We then describe our sampling technique and the resulting coded data. Next, we suggest some directions for the future study of ethnicity and conflict using our bias-corrected data. Our preliminary correlations suggest selection bias may have distorted our understanding about both group and country correlates of ethnic violence.
World Affairs Online
In: The journal of conflict resolution: journal of the Peace Science Society (International), Band 62, Heft 1, S. 203-226
ISSN: 1552-8766
The article introduces the All Minorities at Risk (AMAR) data, a sample of socially recognized and salient ethnic groups. Fully coded for the forty core Minorities at Risk variables, this AMAR sample provides researchers with data for empirical analysis free from the selection issues known in the study of ethnic politics to date. We describe the distinct selection issues motivating the coding of the data with an emphasis on underexplored selection issues arising with truncation of ethnic group data, especially when moving between levels of data. We then describe our sampling technique and the resulting coded data. Next, we suggest some directions for the future study of ethnicity and conflict using our bias-corrected data. Our preliminary correlations suggest selection bias may have distorted our understanding about both group and country correlates of ethnic violence.
In: Journal of peace research, Band 52, Heft 1, S. 110-115
ISSN: 0022-3433
In: Journal of peace research, Band 52, Heft 1, S. 110-115
ISSN: 1460-3578
Protracted conflicts over the status and demands of ethnic and religious groups have caused more instability and loss of human life than any other type of local, regional, and international conflict since the end of World War II. Yet we still have accumulated little in the way of accepted knowledge about the ethnic landscape of the world. In part this is due to empirical reliance on the limited data in the Minorities at Risk (MAR) project, whose selection biases are well known. In this article we tackle the construction of a list of 'socially relevant' ethnic groups meeting newly justified criteria in a dataset we call AMAR (A for All). We find that one of the principal difficulties in constructing the list is determining the appropriate level of aggregation for groups. To address this issue, we enumerate subgroups of the commonly recognized groups meeting our criteria so that scholars can use the subgroup list as one reference in the construction of the list of ethnic groups most appropriate for their study. Our conclusion outlines future work on the data using this expanded dataset on ethnic groups.